Dual hesitant bipolar fuzzy hamacher aggregation operators and their applications to multiple attribute decision making

被引:45
作者
Gao, Hui [1 ]
Lu, Mao [1 ]
Wei, Yu [2 ]
机构
[1] Sichuan Normal Univ, Sch Business, Chengdu 610101, Sichuan, Peoples R China
[2] Yunnan Univ Finance & Econ, Sch Finance, Kunming, Yunnan, Peoples R China
关键词
Multiple attribute decision making (MADM); bipolar fuzzy set; dual hesitant bipolar fuzzy set; dual hesitant bipolar fuzzy Hamacherhybrid average (DHBFHHA) operator; dual hesitant bipolar fuzzy Hamacher hybrid geometric (DHBFHHG) operator; SIMILARITY MEASURES; MEAN OPERATORS; TODIM METHOD; SETS; MODELS;
D O I
10.3233/JIFS-18266
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this paper, we investigate the multiple attribute decision making problems based on the Hamacher aggregation operators with dual hesitant bipolar fuzzy information. Then, motivated by the idea of Hamacher operations, we have developed some Hamacher aggregation operators for aggregating dual hesitant bipolar fuzzy information: dual hesitant bipolar fuzzy Hamacher weighted average (DHBFHWA) operator, dual hesitant bipolar fuzzy Hamacher weighted geometric (DHBFHWG) operator, dual hesitant bipolar fuzzy Hamacher ordered weighted average (DHBFHOWA) operator, dual hesitant bipolar fuzzy Hamacher ordered weighted geometric (DHBFHOWG) operator, dual hesitant bipolar fuzzy Hamacher hybrid average (DHBFHHA) operator and dual hesitant bipolar fuzzy Hamacher hybrid geometric (DHBFHHG) operator. Then, we have utilized these operators to develop some approaches to solve the dual hesitant bipolar fuzzy multiple attribute decision making problems. Finally, a real-world example is then analyzed to illustrate the relevance and effectiveness of the proposed methodology.
引用
收藏
页码:5755 / 5766
页数:12
相关论文
共 79 条
  • [1] Angheluta C, 2013, J MULT-VALUED LOG S, V20, P55
  • [2] MORE ON INTUITIONISTIC FUZZY-SETS
    ATANASSOV, KT
    [J]. FUZZY SETS AND SYSTEMS, 1989, 33 (01) : 37 - 45
  • [3] INTUITIONISTIC FUZZY-SETS
    ATANASSOV, KT
    [J]. FUZZY SETS AND SYSTEMS, 1986, 20 (01) : 87 - 96
  • [4] Fuzzy decision making: A bibliometric-based review
    Blanco-Mesa, Fabio
    Merigo, Jose M.
    Gil-Lafuente, Anna M.
    [J]. JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2017, 32 (03) : 2033 - 2050
  • [5] A Unified Approach to Similarity Measures Between Intuitionistic Fuzzy Sets
    Chachi, J.
    Taheri, S. M.
    [J]. INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS, 2013, 28 (07) : 669 - 685
  • [6] The inclusion-based TOPSIS method with interval-valued intuitionistic fuzzy sets for multiple criteria group decision making
    Chen, Ting-Yu
    [J]. APPLIED SOFT COMPUTING, 2015, 26 : 57 - 73
  • [7] Chiclana F., 2000, P 8 INT C INF PROC M, P985, DOI [10.1007/978-3-7908-1796-6_14, DOI 10.1007/978-3-7908-1796-6_14]
  • [8] Extended Bonferroni Mean Under Intuitionistic Fuzzy Environment Based on a Strict t-Conorm
    Das, Satyajit
    Guha, Debashree
    Mesiar, Radko
    [J]. IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS, 2017, 47 (08): : 2083 - 2099
  • [9] Models for Multiple Attribute Decision Making with Some 2-Tuple Linguistic Pythagorean Fuzzy Hamy Mean Operators
    Deng, Xiumei
    Wang, Jie
    Wei, Guiwu
    Lu, Mao
    [J]. MATHEMATICS, 2018, 6 (11)
  • [10] Models for Safety Assessment of Construction Project With Some 2-Tuple Linguistic Pythagorean Fuzzy Bonferroni Mean Operators
    Deng, Xiumei
    Wei, Guiwu
    Gao, Hui
    Wang, Jie
    [J]. IEEE ACCESS, 2018, 6 : 52105 - 52137